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Probabilistic Methods Surpass Parsimony When Assessing Clade Support in Phylogenetic Analyses of Discrete Morphological Data View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Explore Bristol Research O'Reilly, J., Puttick, M., Pisani, D., & Donoghue, P. (2017). Probabilistic methods surpass parsimony when assessing clade support in phylogenetic analyses of discrete morphological data. Palaeontology. https://doi.org/10.1111/pala.12330 Publisher's PDF, also known as Version of record License (if available): CC BY Link to published version (if available): 10.1111/pala.12330 Link to publication record in Explore Bristol Research PDF-document This is the final published version of the article (version of record). It first appeared online via Wiley at http://onlinelibrary.wiley.com/doi/10.1111/pala.12330/abstract. Please refer to any applicable terms of use of the publisher. University of Bristol - Explore Bristol Research General rights This document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: http://www.bristol.ac.uk/pure/about/ebr-terms [Palaeontology, 2017, pp. 1–14] PROBABILISTIC METHODS SURPASS PARSIMONY WHEN ASSESSING CLADE SUPPORT IN PHYLOGENETIC ANALYSES OF DISCRETE MORPHOLOGICAL DATA by JOSEPH E. O’REILLY1 ,MARKN.PUTTICK1,2 , DAVIDE PISANI1,3 and PHILIP C. J. DONOGHUE1 1School of Earth Sciences, University of Bristol, Life Sciences Building, Tyndall Avenue, Bristol, BS8 1TQ, UK; [email protected]; [email protected]; [email protected]; [email protected] 2Department of Earth Sciences, The Natural History Museum, Cromwell Road, London, SW7 5BD, UK 3School of Biological Sciences, University of Bristol, Life Sciences Building, Tyndall Avenue, Bristol, BS8 1TQ, UK Typescript received 28 April 2017; accepted in revised form 13 September 2017 Abstract: Fossil taxa are critical to inferences of historical 50% support. Ignoring node support, Bayesian inference is diversity and the origins of modern biodiversity, but realizing the most accurate method in estimating the tree used to sim- their evolutionary significance is contingent on restoring fossil ulate the data. After assessing clade support, Bayesian and species to their correct position within the tree of life. For Maximum Likelihood exhibit comparable levels of accuracy, most fossil species, morphology is the only source of data for and parsimony remains the least accurate method. However, phylogenetic inference; this has traditionally been analysed Maximum Likelihood is less precise than Bayesian phylogeny using parsimony, the predominance of which is currently estimation, and Bayesian inference recaptures more correct challenged by the development of probabilistic models that nodes with higher support compared to all other methods, achieve greater phylogenetic accuracy. Here, based on simu- including Maximum Likelihood. We assess the effects of these lated and empirical datasets, we explore the relative efficacy of findings on empirical phylogenies. Our results indicate proba- competing phylogenetic methods in terms of clade support. bilistic methods should be favoured over parsimony. We characterize clade support using bootstrapping for parsi- mony and Maximum Likelihood, and intrinsic Bayesian pos- Key words: phylogenetic analysis, morphology, parsimony, terior probabilities, collapsing branches that exhibit less than Maximum Likelihood, Bayesian, Mk model. T HE goal of reconstructing an holistic Tree of Life has majority rule consensus tree constructed from a sample been envisaged since the inception of evolutionary theory. of trees from the posterior distribution (hereafter the This entails not only the use of molecular phylogenetics Bayesian tree) as optimality trees (following Holder et al. to determine the inter-specific relationships between 2008) and compared them directly to the optimal Maxi- extant taxa, but also the restoration of extinct branches to mum Likelihood and Maximum Parsimony trees. How- the Tree of Life. For the majority of extinct species, this ever, because Bayesian trees have intrinsic support values can only be achieved through phylogenetic analysis of (posterior probabilities) some have argued that they morphological data. Parsimony has dominated the phylo- should be compared to bootstrapped Maximum Likeli- genetic analysis of morphological data but its hegemony hood trees (Huelsenbeck et al. 2001), even though post- is now challenged by model-based phylogenetic methods erior probabilities and bootstrap proportions are neither that attempt to approach the realism of models of evolu- interchangeable nor directly comparable (Douady et al. tion developed for molecular evolution (Lewis 2001). 2003). Brown et al. (2017) showed that, when clade Simulation-based studies have shown that parsimony is support is considered, Maximum Likelihood and Bayesian less accurate than Bayesian analysis for phylogenetic infer- implementations of the Mk model are effectively indistin- ence with morphological data (Wright & Hillis 2014; guishable in terms of topological accuracy. O’Reilly et al. 2016; Puttick et al. 2017). Previous studies Here we develop upon previous studies to incorporate (O’Reilly et al. 2016; Puttick et al. 2017) treated the 50% measures of clade support in the investigation of the © 2017 The Authors. doi: 10.1111/pala.12330 1 Palaeontology published by John Wiley & Sons Ltd on behalf of The Palaeontological Association. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. 2 PALAEONTOLOGY performance of parsimony relative to Maximum Likeli- and the shape of the gamma distribution of character- hood and Bayesian implementations of the Mk model in wise rate heterogeneity were sampled independently from the phylogenetic analyses of morphological data. An ini- an exponential distribution of mean 1, ensuring a reason- tial comparison of the accuracy and resolution of differ- able level of rate heterogeneity between replicate datasets ent methods is achieved through the use of simulated and between the constituent characters of each replicate data. We take a simulation-based, rather than an empiri- matrix. The choice of rate parameters in our simulation cal approach since the performance of phylogenetic meth- framework is validated by our ability to easily simulate ods in tree estimation can only be assessed when the tree matrices with empirical levels of homoplasy. To ensure is known; this is never the case for empirical data. Empir- data did not collapse into the Mk model and therefore ical analyses are performed to demonstrate the influence unintentionally provide a benefit when applying the Mk of methods on the testing of phylogenetic hypotheses. We model for phylogenetic inference, we applied an unequal compare clade support using standard methods, with pos- stationary distribution of p = [0.2, 0.2, 0.3, 0.3] in the terior probabilities obtained from posterior samples of HKY model. Fixing the stationary distribution in this Bayesian trees and non-parametric bootstrap proportions manner enforces violation of the assumptions of the Mk calculated for most-parsimonious and Maximum Like- model that the limiting distribution of character states is lihood trees, collapsing poorly-supported (nodes with equal and that transitions between any two character states < 0.5 posterior probability, or present in < 50% of boot- are equally probable. A mixture of binary and multistate strap replicates) nodes in trees constructed with each characters was simulated, with binary characters obtained method. We find that parsimony has low accuracy com- through the R/Y (purine/pyrimidine) recoding of molecu- pared to both Bayesian and Maximum Likelihood imple- lar data as character states of 0 or 1, resulting in the elimi- mentations of the Mk model. However, the Bayesian nation of the transition–transversion ratio for these implementation still achieves higher support values on characters and an effective stationary distribution of correct nodes than does the Maximum Likelihood imple- p = [0.4, 0.6], which is a violation of the assumption of mentation. Based on these results, we conclude that a the Mk model that character states exhibit an even limiting Bayesian implementation of the Mk model should be pre- distribution. Multistate characters were obtained by recod- ferred over the Maximum Likelihood implementation ing nucleotide data as character states of 0, 1, 2, or 3, when analysing categorical morphological data. Neverthe- depending on the nucleotide present at each terminal. The less, both implementations are superior to parsimony final ratio of binary to multistate characters in each matrix when analysing categorical morphological data. was 55:45, based on the mean ratio observed in empirical data (Guillerme & Cooper 2016). For each of the 100, 350, and 1000 character sets we generated 1000 matrices that, MATERIAL AND METHOD in total, exhibited a distribution of homoplasy approxi- mating that reported by Sanderson & Donoghue (1996). Simulated data Goloboff et al. (2017) have criticized this approach to simulating morphology-like datasets on the basis that our For all analyses, we estimated topologies and support val- generating trees encompass only contemporaneous taxa, ues using datasets of 100, 350, and 1000 characters from assume that evolutionary rates are constant across time Puttick et al. (2017), simulated on both the asymmetrical and the tree, and
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